The orientation field, or orientation, of an image may be used as important information for parsing the image. For example, in the field of image searching in which many images are searched for important images, and in the field of image tracking field, in which a predetermined object, such as a person or a car, is tracked from moving pictures, the orientation field of the image is used intensively. For this reason, technologies for accurately analyzing the orientation field of an image have been actively researched in a variety of fields.
In particular, since in the fingerprint recognition field, fingerprint recognition is performed by using the shape of ridges and valleys of a fingerprint, technology for accurately estimating the orientation field of a fingerprint, and the orientation of the ridges in particular, from a fingerprint image is important. Because of this importance, many research activities for technologies for measuring the orientation field of a fingerprint quickly and accurately have been conducted.
Among these technologies, representative ones include a technology for measuring the orientation field of a fingerprint using a neural net theory, a technology for measuring the orientation field of a fingerprint using an image filter, and a technology for measuring the orientation field using gradient information calculated from the brightness of pixels in a fingerprint image. In particular among them, the technology measuring the orientation field by using the gradient information is widely used.
A fingerprint recognition system is a system for identifying an individual by using characteristics of a fingerprint that are different in each individual, and by using the orientation field of a fingerprint in particular.
FIG. 1 is a block diagram of the structure of an ordinary fingerprint recognition system.
As shown in FIG. 1, the fingerprint recognition system includes a fingerprint image acquisition unit 110, a fingerprint region extraction unit 130, an orientation estimation unit 150, a fingerprint characteristic extraction unit 170, a fingerprint recognition unit 190, and a fingerprint characteristic storage unit 195.
The fingerprint image acquisition unit 110 obtains a fingerprint image and can include a fingerprint recognition sensor to obtain only a fingerprint image, and/or can also include a camera embedded in a digital camera or a mobile phone.
The fingerprint region extraction unit 130 extracts only a fingerprint region excluding a background in an obtained fingerprint image. The fingerprint orientation estimation unit 150 estimates the orientation field of a fingerprint using the structure of the ridges and valleys of the fingerprint in the extracted fingerprint region. In order to estimate the orientation field of the fingerprint, the orientation measuring technologies described above have been used.
The fingerprint characteristic extraction unit 170 extracts the fingerprint characteristics using the orientation field of the fingerprint. The extracted fingerprint characteristics are stored in the fingerprint characteristic storage unit for fingerprint recognition. When fingerprint recognition is performed, the fingerprint recognition unit 190 performs fingerprint recognition by comparing the fingerprint characteristics extracted in the fingerprint characteristic extraction unit 170 with the fingerprint characteristics stored in the fingerprint characteristic storage unit 195.
As described above, the fingerprint characteristics are extracted using the orientation field of the fingerprint and accordingly, accurate and fast estimation of the orientation field of the fingerprint is one of major subjects in the fingerprint recognition field.
In general, when a clear fingerprint image can be obtained as in a fingerprint sensor, the orientation of the fingerprint can be easily and accurately measured. However, when a clear fingerprint image cannot be obtained, for example, when a fingerprint image is obtained using an image taking apparatus, such as a digital camera and/or a mobile phone camera, the orientation of the fingerprint may not be measured accurately. In particular, when a fingerprint image is distorted by strong external light, camera noise or a variety of factors (for example, too soft skin as those of children and women, a moist finger, and a finger with a wound), an incorrect orientation of the fingerprint may be detected.
FIG. 2 illustrates dome forms of distortion that can occur when a fingerprint image is obtained using a camera.
Broadly speaking, five types of distortions can occur in a fingerprint image obtained using a camera under illuminations such as sunlight and/or camera flash.
The first distortion is caused by the curved circumferential shape of a finger. As shown in regions 1 and 1′ of FIG. 2, the interval between a ridge and a valley of a fingerprint is uniform in a region (region 1) which is level in relation to the direction of a camera lens, while both sides of the finger are sloping in relation to the direction of the camera lens and the interval between ridges and valleys gradually narrows (region 1′).
The second distortion occurs because of the protruded part of the center of the fingertip. As shown in region 2 of FIG. 2, the shape of the ridge is clear in the central part of the finger, but the side part of the finger has a shade such that the shape of the ridge becomes unclear.
The third distortion occurs due to wounds such as scars and/or burns on the finger skin. As shown in region 3 of FIG. 2, when a wound is on the finger skin, an artificial valley is formed and thus, when the orientation of the fingerprint is measured, a ridge orientation that is totally different from that of the actual ridge orientation can be measured.
The fourth distortion is also caused by the protruded part of the center of the fingertip. As shown in region 4 of FIG. 2, a blurring phenomenon occurs in which due to the protruded part of the fingertip, focusing becomes partially incorrect to make the image blurred.
The fifth distortion occurs by illumination existing when a fingerprint image is taken by a camera. That is, when a fingerprint image is taken by a camera, illumination such as camera flash light and/or sunlight can be applied to the finger. As shown in region 5 of FIG. 2, when the illumination is applied, a phenomenon in which a predetermined region of the fingerprint image is too bright can occur.
Besides, when the skin of the finger is too soft as in those of children and women, or when the finger is too moist, distortion can occur in the fingerprint image.
However, according to the conventional orientation measuring technologies, when a clear fingerprint image cannot be obtained, as when a fingerprint image is obtained using an image taking apparatus, such as a digital camera and/or a mobile phone camera, the orientation of the fingerprint may not be measured accurately, and in particular, when there is distortion in the fingerprint image, an incorrect orientation field of the fingerprint can be obtained.